Nathalie Popiolek, Senior Expert

Transcription

1 MULTI CRITERIA ANALYSIS OF INNOVATION POLICIES IN FAVOR OF SOLAR MOBILITY IN FRANCE IN 2030 Nathalie Popiolek, Senior Expert 33 RD USAEE/IAEE NORTH AMERICAN CONFERENCE N. Popiolek, 33RD USAEE/IAEE North 21 OCTOBRE 2015OCT 25-28, American 2015, Conference, PITTSBURG Oct 25-28, 2015, PAGE 1 Pittsburg THE AIM OF THE RESEARCH An analysis from the point of view of the public authorities of various innovation policies for the deployment in France in 2030 of electric vehicles powered by solar photovoltaic electricity (PV) This innovation involves creating synergy between buildings and mobility by associating positive energy houses (with PV panels on their roofs) with electric vehicles (EVs). The batteries of these vehicles would be primarily recharged by PV electricity and could also be a way for stocking intermittent solar electricity for later use. 21 OCTOBRE 2015 PAGE 2 1

2 SOLAR MOBILITY CONCEPT Recharging the Battery Photovoltaic electricity first Positive Energy House Work Place Stocking Electricity for later Use Power Grid PAGE 3 METHODOLOGY 1 Innovation Policy instruments Analysis 2 Case studies for 2030 with CO 2 Evaluation and Total Cost of Ownership 3 Impact evaluation of Public Policies Deployment 4 Multi criteria Comparison of Public Policies 21 OCTOBRE 2015 PAGE 4 2

3 CASE STUDY Recharging Modalities Network Home Workplace At home At home and at Work Only at Work PAGE 5 RESULTS FOR AN INDIVIDUAL FAMILY (2030) CO 2 for solar mobility compared to fuel mobility without PV CO 2 emissions Savings : 24% to 46% depending on climate, the distance traveled daily to go to work and the modalities of battery charging Total Cost of Ownership compared to fuel mobility without PV Cost savings : 12% (cheaper) to - 3% (more expensive) The TCO decreases when the Vehicle covers greater distances (see : Taverdet-Popiolek N., Quenard D., Thais F., Vinot S., Wiss O., 2013) 21 OCTOBRE 2015 PAGE 6 3

4 IMPLEMENTATION OF A DECISION-MAKING MODEL For the public administration which can select the best innovation policies based on criteria reflecting their major goals in terms of policies concerning energy, economics, social consistency, "factor 4" = reduce CO 2 emissions by 4 in 2050 compared to its level in 1990 (French Law POPE, July 2005) N. POPIOLEK, 21 OCTOBRE 33 RD 2015 USAEE/IAEE NORTH AMERICAN CONFERENCE, OCT 25-28, 2015, PITTSBURG PAGE 7 METHODS Identify different innovation policies Strengthen or combine coherently their instruments policy of supply (subsidy to R&D) or demand (investment aid for users, feed-in tariff) environmental and fiscal policies (carbon tax, gas tax) policies of territorial planning and the social cohesion (investment aid for regions, smart-cities ) Elaborate the criteria based on the main objectives of the public authorities one criterion for each objective plus a criterion reflecting the public cost discounted over the study period of the deployment of any tool 21 OCTOBRE 2015 PAGE 8 4

5 Economics Context Sociological Context Industrial Context Policies of Supply Policies instruments RESULTS / CRITERIA Policies of Demand Environmental and fiscal policies Policies of territorial planning and social cohesion R&D Subsidies Investment Aids feed-in tariff Carbon Tax Fuel tax CO 2 balance State Budget: expenditure Health and Pollution Job creation Peak smoothing Avoided Imports Acceptability Diffusion in the North PAGE 9 A TOTAL OF EIGHT CRITERIA WERE SELECTED AND WEIGHTED 30% Weight of the criterion 22% 8% 8% 8% 8% 8% 8% PAGE 10 5

6 EVALUATION OF EACH CRITERION For each combination of instruments, all criteria are evaluated compared to the Business As Usual Policy, reflecting the continuity of the current policy until 2030 in the context of a relatively favourable economic and energy scenario for solar mobility in France during the study period -high gas and electricity prices : positive annual growth rate over [2015, 2050] -low discount rate : 5% N. POPIOLEK, 21 OCTOBRE 33 RD 2015 USAEE/IAEE NORTH AMERICAN CONFERENCE, OCT 25-28, 2015, PITTSBURG PAGE 11 OUTRANKING APPROACH We choice ELECTRE IS method (Roy B., 1991; Roy B. and Skalka J.M., 1987) For each criterion (j), we take into account a threshold of indifference (q j ). This is related to the fact that the statistics we use have uncertainties because they have been projected in time (evaluation of the criteria over the period [2015, 2050] taking into account the length of mobilized equipment life) to the difficulty for the public authorities to express strict preferences for local ranking, on the criteria, for two actions with very similar assessments 21 OCTOBRE 2015 PAGE 12 6

7 The concordance level is set at 0.8 as is frequently the case with ELECTRE IS 80% of weighted criteria must vote "yes" to the statement "the a policy is better than the b policy" in order to say a outranks b at the global level. PAGE 13 WEIGHT OF CRITERIA AND INDIFFERENCE THRESHOLD Criterion Units Preferences Branch 1. CO 2 balance: avoided emissions Weight of the criterion k j Threshold of indifference Million t Max 30% 4 2. State Budget: expenditure Million Min 22% 1000 q j 3. Health and Pollution: avoided cost Million Max 8% Job creation Thousands of jobs Max 8% Avoided Imports Million Max 8% Diffusion in the North of % Max 8% 0 France 7. Acceptability Points Max 8% 0 8. Peak smoothing Cumulative hours Max 8% OCTOBRE 2015 PAGE 14 7

8 ELECTRE SIMULATION Simulations for policies families Policies of Supply Kernel 1 Mixed Policies Kernel 3 Policies of demand Kernel 2 Etc. Kernel Simulations for adopted policies Kernels successful policies N. POPIOLEK, 21 OCTOBRE 33 RD 2015 USAEE/IAEE NORTH AMERICAN CONFERENCE, OCT 25-28, 2015, PITTSBURG PAGE Mt 40 Mt 40 Mt RESULTS FOR FAVORABLE SCENARIO FOR THE COMPETITIVENESS OF FRANCE 4000 M 750 M 800 M Successful Policies P1 = R&D Subsidies (PV + EV) + carbon tax P2 = R&D Subsidies (PV, EV + Smart-Grid) + carbon tax P3 = Feed-in-tariffs + carbon tax Carbon tax = 44 /tco 2 at 2015, 100 at 2030 and 200 at 2050 PAGE 16 8

9 CONCLUSIONS Results for favorable scenario A demand policy (P 3 ) based on a strengthening of Feed-intariffs in 2015 with a carbon tax, is among the best policies. It has the disadvantage of not being very focused on mobility because it only subsidizes photovoltaic electricity. We preferred to recommend to the public authorities the two ring policies (P 1 ) and (P 2 ) that simultaneously combine a research support in favor of related technologies and a relatively high carbon tax. The results seem to be confirmed in the case of an unfavorable competitive scenario. Such a result is in the same direction as the work with a different methodology (endogenous growth models applied to low-carbon energy technologies) (see Taverdet-Popiolek N. et al., 2013). N. POPIOLEK, 21 OCTOBRE 33 RD 2015 USAEE/IAEE NORTH AMERICAN CONFERENCE, OCT 25-28, 2015, PITTSBURG PAGE 17 REFERENCES Roy B., 1991, The outranking approach and the foundations of ELECTRE methods. Theory and decision 31, Roy B., Skalka J.M., 1987, ELECTRE IS, Aspects Méthodologiques et guide d utilisation, Document du Lamsade, n 30, Uni versité Paris Dauphine, France. Taverdet-Popiolek N., Berwald A., Lafforgue G., 2013, A note on the induced effects of carbon prices and R&D subsidies in carbon-free technologies, Energy studies review, mars 2013, Vol. 20, Iss. 2, Art. 4, pp Taverdet-Popiolek N., Quenard D., Thais F., Vinot S., Wiss O., 2013, Mettre l innovation sur la trajectoire du facteur 4: la mobilité solaire en 2030, Revue de l énergie 611, PAGE 18 9

10 Thank you for your attention! PAGE 19 ANNEX N. Popiolek, 33 RD USAEE/IAEE North American Conference, Oct 25-28, 2015, Pittsburg PAGE 20 10

11 CO 2 EMISSIONS SAVINGS COMPARED TO FUEL MOBILITY WITHOUT PV (REF) g CO2/km energy supplied % -24% -39% -30% -33% -46% vehicule consumption vehicle manufacturing battery manufacturing 0-50 Réf 1a 1b 1c 1d 1e 1f electric appliance Distance traveled daily to go to work = 50 km 21 OCTOBRE 2015 PAGE 21 CO 2 EMISSIONS SAVINGS g CO2/km % -32% -26% -38% -38% -46% Réf 2a 2b 2c 2d 2e 2f Distance traveled daily to go to work = 16km energy supplied vehicule consumption vehicle manufacturing battery manufacturing electric appliance PAGE 22 11

12 TOTAL COST OF OWNERSHIP COMPARED TO FUEL MOBILITY WITHOUT PV Distance traveled daily to go to work = 50 km 3,4% 3,3% 3,4% 1,1% Ref1 1a 1b 1c 1d 1e 1f Ref2 2a 2b 2c 2d 2e 2f -1,4% -1,1% -1,0% -3,5% -5,7% -5,7% Distance traveled daily to go to work = 16 km -11,7% -11,7% PAGE 23 ENERGY AND ECONOMIC CONTEXT Oil price ($/bl) Annual growth rate High [ ] : 2,8% [ ] : 1,8% Low [ ] : 1% [ ] : -0,5% Electricity price ( /MWh) Annual growth rate High [ ] : 1,9% [ ] : 0,5% Low [ ] : 0,4% [ ] : -0,2% Discount rate 5% 7% Scenario of context for Energy and Economy Favorable Unfavorable PAGE 24 12

13 NUMBER OF VEHICLES LOADED WITH SOLAR ELECTRICITY IN FRANCE 4,5 4 3,5 3 2,5 2 1, ,5 0 Policies of supply (14 GW PV at 2030) Policies of demand (20 to 24 GW PV at 2030) Mixed Policies (17 to 21 GW PV en 2030) Mixed Policies with "smart cities" (4 GW PV at 2030) N. POPIOLEK, 21 OCTOBRE 33 RD 2015 USAEE/IAEE NORTH AMERICAN CONFERENCE, OCT 25-28, 2015, PITTSBURG PAGE 25 POLICIES CONTAINED IN THE KERNEL AND EVALUATION CRITERIA Kernel s policies (final stage) CO 2 balance (Mt of avoided CO 2 ) State Budget (M ) Health and Pollution (avoided cost M ) Jobs created (thousands) Avoided Imports (M ) North diffusion (%) Population Acceptability (points) Peak Smoothing (hours) P P P OCTOBRE 2015 PAGE 26 13